Basic Principles in Flow Cytometry. Flow Cytometry

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1 Basic Principles in Flow Cytometry Flow Cytometry» Flow Cytometry is the technological process that allows for the individual measurements of cell fluorescence and light scattering. This process is performed at rates of thousands of cells per second.» This information can be used to individually sort or separate subpopulations of cells.

2 History Flow cytometry developed from microscopy. Thus Leeuwenhoek is often cited in any discussion regarding it s history. F.T. Gucker (1947)build the first apparatus for detecting bacteria in a LAMINAR SHEATH stream of air. L. Kamentsky (IBM Labs), and M. Fulwyler (Los Alamos Nat. Lab.) experimented with fluidic switching and electrostatic cell sorters respectively. Both described cell sorters in M. Fulwyler utilized Pulse Height Analyzers to accumulate distributions from a Coulter counter. This feature allowed him to apply statistical analysis to samples analyzed by flow.

3 History In 1972 L. Herzenberg (Stanford Univ.), developed a cell sorter that separated cells stained with fluorescent antibodies.the Herzenberg group coined the term Fluorescence Activated Cell Sorter (FACS).

4 Fluorescence Activation Process (or Immunofluorescence) Antibodies recognize specific molecules in the surface of some cells Antibodies are artificially conjugated to fluorochromes FITC FITC Antibodies FITC FITC When the cells are analyzed by flow cytometry the cells expressing the marker for which the antibody is specific will manifest fluorescence. Cells who lack the marker will not manifest fluorescence But not others

5 Cellular Parameters Measured by Flow Intrinsic Extrinsic No reagents or probes required (Structural) Cell size(forward Light Scatter) Cytoplasmic grabularity(90 degree Light Scatter) Photsynthetic pigments Reagents are required. Structural DNA content DNA base ratios RNA content Functional Surface and intracellular receptors. DNA synthesis DNA degradation (apoptosis) Cytoplasmic Ca++ Gene expression

6 Flow Cytometry Applications Immunofluorescence Cell Cycle Kinetics Cell Kinetics Genetics Molecular Biology Animal Husbandry (and Human as well) Microbiology Biological Oceanography Parasitology Bioterrorism

7 Flow cytometry integrates electronics, fluidics, computer, optics, software, and laser technologies in a single platform.

8 Z Y X Sample Sheath Cells are presented to the laser using principles of hydrodynamic focusing Flow chamber Y Z Laser optics Laser Beam X

9 Laminar Fluidic Sheath Core Sheath FITC FL PE FL Outer Sheath 488nm Sct

10 Each cell generates a quanta of fluorescence Photomultiplier Tubes (PMT s) PE FL FITC FL 488nm Sct Discriminating Filters Dichroic Lenses Confocal Lens Forward Light Scattering Detector

11 Negative cells are also detected PE FL FITC FL 488nm Sct Dichroic Lenses Confocal Lens Forward Light Scatter

12 Optical Bench Schematic FL2 Sensor 575BP FL3 Sensor 620BP FL4 Sensor 675BP FL1 Sensor 525BP SS Sensor Fluorescence Pickup Lens 600DL 645DL Laser Beam 488BK 550DL 488DL Flow Cell FS Sensor

13 From Fluorescence to Computer Display Individual cell fluorescence quanta is picked up by the various detectors(pmt s). PMT s convert light into electrical pulses. These electrical signals are amplified and digitized using Analog to Digital Converters (ADC s). Each event is designated a channel number (based on the fluorescence intensity as originally detected by the PMT s) on a 1 Parameter Histogram or 2 Parameter Histogram. All events are individually correlated for all the parameters collected.

14 Light Scattering, 2 Parameter Histogram Bigger 90 degree Light Scatter Y Axis Apoptotic Cells Dead Cells Bigger Cells More Granular X Axis Forward Light Scatter (FLS) Live Cells

15 1 Parameter Histogram Negative Positive Count Dimmer Brighter Channel Number Fluorescence picked up from the FITC PMT

16 Single Positive PI Population 2 Parameter Histogram Double Positive Population PE FL Negative Population FITC FL Single Positive FITC Population

17 Gating and Statistics Data generated in flow cytometry is displayed using Multiparamater Acquisition and Display software platforms. Histograms corresponding to each of the parameters of interest can be analyzed using statistical tools to calculate percentage of cells manifesting specific fluorescence, and fluorescence intensity. This information can be used to look at fluorescence expression within subpopulations of cells in a sample (gating).

18 Flow Cytometry Data Smaller Region, Live cells mostly Larger Region includes all cells

19 Running Samples Prepare samples. One sample should be completely negative. This sample should be analyzed first. This sample is used for adjusting the PMT s amplification voltage. Adjust the PMT Voltage until you can see a population peak in the first decade of your 1 parameter and or your two parameter plot.these samples are used for adjusting Spectral Overlap. Once the instrument settings are optimized, run samples and collect data.

20 Flow Cytometry and sorting